Hijacking the unfolded protein response (UPR) pathway: Balancing viral infection and host cell survival
Bibliographic record
Abstract
The endoplasmic reticulum (ER) unfolded protein response (UPR) is a conserved eukaryotic pathway crucial for restoring cellular homeostasis under ER stress. However, diverse viruses infecting mammalian or plant cells strategically hijack and manipulate the UPR pathways featuring sensor proteins IRE1, PERK, ATF6, and bZIP17/28 to promote viral replication. While UPR is designed to provide cellular adaptive functions in response to stresses, viruses can instead exploit UPR components to instead enhance viral protein folding and remodel ER membranes for viral replication. Exploiting the UPR presents a critical dilemma: while mild UPR activation facilitates virus replication and survival, excessive or prolonged activation triggers host programmed cell death (PCD), prematurely terminating infection. Navigating this UPR tightrope is central to successful infection and replication of the virus. Viruses are not passive triggers of ER stress and the UPR. Viruses have evolved sophisticated "braking mechanisms" to actively modulate UPR signaling intensity. By fine-tuning the UPR, viruses harness the beneficial aspects of the UPR while crucially preventing the activation cascade from reaching the lethal threshold that initiates PCD. By carefully controlling the UPR balance, viruses ensure host cell survival for a sufficient duration to maximize viral progeny production. This review details the intricate interactions between the cellular UPR and infecting viruses, including links to cellular clearance pathways like autophagy and ER-associated degradation (ERAD), across different viral families (flaviviruses, coronaviridae, and potyviruses) and hosts (plants and animals). Understanding the sophisticated viral manipulation of the UPR equilibrium reveals fundamental insights into host-pathogen co-evolution and highlights novel potential targets for antiviral strategies aimed at disrupting this delicate balance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".